Near-field U-MIMO communications require carefully optimized sampling grids in both angular and distance domains. However, most existing grid design methods neglect the influence of base station height, assuming instead that the base station is positioned at ground level - a simplification that rarely reflects real-world deployments. To overcome this limitation, we propose a generalized grid design framework that accommodates arbitrary base station locations. Unlike conventional correlation-based approaches, our method optimizes the grid based on the minimization of the optimal normalized mean squared error, leading to more accurate channel representation. We evaluate the performance of a hybrid U-MIMO system operating at sub-THz frequencies, considering the P-SOMP algorithm for channel estimation. Analytical and numerical results show that the proposed design enhances both channel estimation accuracy and spectral efficiency compared to existing alternatives.

翻译：近场U-MIMO通信需要在角度域和距离域同时进行精心优化的采样网格设计。然而，现有的大多数网格设计方法忽略了基站高度的影响，通常假设基站部署在地面水平——这种简化假设很少符合实际部署场景。为克服这一局限，我们提出了一种适用于任意基站位置的广义网格设计框架。与传统基于相关性的方法不同，本方法通过最小化最优归一化均方误差来优化网格，从而实现更精确的信道表示。我们评估了工作在亚太赫兹频段的混合U-MIMO系统性能，其中采用P-SOMP算法进行信道估计。解析与数值结果表明，相较于现有方案，所提出的设计在信道估计精度和频谱效率方面均有显著提升。